The King Lab

@ The University of Missouri

Genetics of Complex Traits: The Drosophila Synthetic Population Resource (http://FlyRILs.org)

My lab is part of a collaborative project to develop a new community resource for the genetic dissection of complex traits in Drosophila melanogaster. The Drosophila Synthetic Population Resource (DSPR) is a large collection of recombinant inbred lines derived from an 8-way 50 generation intercross. This design creates a panel of lines whose genomes are a mosaic of the original 8 founder lines, allowing for unprecedented mapping resolution for a linkage-based panel. We are primarily involved in processing the genomic data, describing the genetic properties of the resource, and developing the analytical tools for QTL mapping using the DSPR. For much more information, visit http://FlyRILs.org

Genetic Basis of Allocation Pathways

Allocation strategies are highly complex traits and require a systems level approach to uncovering their genetic basis. The allocation of resources is thought to influence nearly all the major structures and functions of an organism, is affected by an array of interacting physiological pathways, varies across the lifetime of the organism, and interacts with many different environmental factors. This underlying complexity makes identifying most of the causative genetic variants very challenging. While the physiological mechanisms underlying the metabolism and allocation of nutrients are fairly well understood and many of the major genes encoding the proteins in these physiological pathways are known, very little is known about the source of natural variation in allocation.

Our lab takes approaches such as focusing directly on known allocation pathways (such as the D. melanogaster insulin/insulin-like signaling pathway shown here) and mapping transcript abundance for the key genes in those pathways in multiple nutritional conditions. We use the DSPR (see above) for this work with the long term goal of elucidating the relationship between causative genetic variants, environmental influences, transcriptome level phenotypes, physiological phenotypes, and visible phenotypes.

Mathematical Modeling of the Evolution of Flexible Allocation Strategies

Wing dimorphic insects are a model system for studying resource allocation strategies. In these insects, there is a well-studied trade-off between allocation to flight capability and reproduction. This trade-off is most dramatic between the two discrete morphs with the flight capable morph having a lower reproductive output than the flightless morph, though the trade-off also occurs within flight capable morphs.

One of the main research directions in the lab is elucidating how variation in resource availability in the environment can select for flexible allocation strategies, given that the optimal allocation strategy can be very different depending on the amount of resources available to an organism. Examples of shifts in resource allocation in response to variation in resource levels in natural populations are common, however, few theoretical models exist to predict how the phenotypic plasticity in allocation is expected to evolve. We have previously developed quantitative genetic simulation models predicting the evolved allocation reaction norm in response to varying acquisition regimes using the wing dimorphic insect system, and this work is ongoing.